A Data Science Process, Documentation, and Project Template You Can Use in Your Solutions
In most of the Data Science and AI articles, blogs and papers I read, the focus is on a particular algorithm or math angle to solving a puzzle. And that's awesome - we need LOTS of those. However, even if you figure those out, you have to use them somewhere. You have to run that on some sort of cloud or local system, you have to describe what you're doing, you have to distribute an app, import some data, check a security angle here and there, communicate with a team....you know, DevOps. In this article, I'll show you a complete process, procedures, and free resources to manage your Data Science project from beginning to end.Understanding AWR Data for Exadata to Azure IaaS Migrations, Part I
High IO workloads in Azure are a topic of common interest and of those workloads, Oracle Exadata tops the list. I’m going to begin to post about how the Oracle on Azure SMEs in the Cloud Architecture and Engineering team handle those.Oracle Workloads on Azure- IO is King!
If you’re migrating your data estate to Azure, as is normal considering we are an enterprise cloud that can be the home for all your data, including Oracle, you may wonder what storage solutions there are. You didn’t realize how important storage was? Most customers we meet with are focused on what vCPU and memory are available, but for 95% of Oracle workloads, it’s IO that makes the decision on the infrastructure we choose and of that IO, its throughput, (MBPs) that is most often the deciding factor. This post isn’t going to be about promoting one storage vendor or any solution over another, but hopefully help you understand that each customer engagement is different and that there is a solution for everyone, and you can build out what you need and meet every IO workload with Oracle in Azure.Using Oracle AWR and Infra Info to Give Customers Complete Solutions to Performance Problems
One of the best allocations of an Oracle SME specialist at Microsoft is when there is a complex data/infra issue for one of our customers. We have a unique set of skills, understanding relational workloads along with deep infrastructure knowledge combined to identify issues that may be missed without these skills.
